Low-mass-ion discriminant equation (LOME) for ovarian cancer screening

Abstract

BackgroundA low-mass-ion discriminant equation (LOME) was constructed to investigate whether systematic low-mass-ion (LMI) profiling could be applied to ovarian cancer (OVC) screening.ResultsMatrix-assisted laser desorption/ionization-time of flight (MALDI-TOF) mass spectrometry was performed to obtain mass spectral data on metabolites detected as LMIs up to a mass-to-charge ratio (m/z) of 2500 for 1184 serum samples collected from healthy individuals and patients with OVC, other types of cancer, or several types of benign tumor. Principal component analysis-based discriminant analysis and two search algorithms were employed to identify discriminative low-mass ions for distinguishing OVC from non-OVC cases. OVC LOME with 13 discriminative LMIs produced excellent classification results in a validation set (sensitivity, 93.10 %; specificity, 100.0 %). Among 13 LMIs showing differential mass intensities in OVC, 3 metabolic compounds were identified and semi-quantitated. The relative amount of LPC 16:0 was somewhat decreased in OVC, but not significantly so. In contrast, D,L -glutamine and fibrinogen alpha chain fragment were significantly increased in OVC compared to the control group (p = 0.001 and 0.002, respectively).ConclusionThe present study suggested that OVC LOME might be a useful non-invasive tool with high sensitivity and specificity for OVC screening. The LOME approach could enable screening for multiple diseases, including various types of cancer, based on a single blood sample. Furthermore, the serum levels of three metabolic compounds—D,L -glutamine, LPC 16:0 and fibrinogen alpha chain fragment—might facilitate screening for OVC.Electronic supplementary materialThe online version of this article (doi:10.1186/s13040-016-0111-7) contains supplementary material, which is available to authorized users.

Reduced levels of N’-methyl-2-pyridone-5-carboxamide and lysophosphatidylcholine 16:0 in the serum of patients with intrahepatic cholangiocarcinoma, and the correlation with recurrence-free survival

“…The metabolic ion of (negative) 167.0211 m/z with an RT of 2.48 min was shown to have originated from uric acid (HMDB00289) (Figure 4 ). Two other metabolic ions (of 496.3398 m/z with an RT of 14.977 min and 768.8499 m/z with an RT 7.544 min) had been identified as LPC 16:0 [ 12 ] and fibrinopeptide A [ 9 ], respectively, in our previous studies.…”

“…Recently, we analyzed metabolites that were detected as low-mass ions by mass spectrometry (MS), and reported the metabolic profiles of biofluids (including urine and serum) of cancer patients. The data were useful for the early cancer diagnosis and prediction of prognosis [ 9 – 15 ]. Here, we described the MS-based metabolic profile of serum from IHCC patients, and explored the clinical significance of the upregulation of N’-methyl-2-pyridone-5-carboxamide levels in these patients.…”

Performance of matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF-MS) in diagnosis of ovarian cancer: a systematic review and meta-analysis

“…Lee et al showed that the best PLR and NLR was respectively 44.17 and 0.13. The reason why the result showed the good performance is that low-mass-ion (LMI) profiling was constructed to screen for OC with the removal of high-abundant peptide and protein [20]. Therefore, the high-abundant protein in serum or plasma should be separated to improve the discovery of meaningful markers when MALDI-TOF-MS is used to differentiate the ovarian cancer.…”

“…Seven articles were included in the meta-analysis [15][16][17][18][19][20][21], according to the inclusion and exclusion criteria. The flowchart summarized the process of selection ( Fig.…”

Cerebrospinal fluid metabolomic profiles can discriminate patients with leptomeningeal carcinomatosis from patients at high risk for leptomeningeal metastasis

“…This apparently increased number of LMIs might have contributed to the ability to discriminate Group 2 from groups of 1a/3/4 at values of 85% sensitivity and 91% specificity, but the number of LMIs is not necessarily proportional to the accuracy. Unlike our two prior studies [ 11 , 16 ], we applied the LOME scheme to the triple-TOF MS data in this study, selected the LOMEs (LOME 1-33 and 2-21), and obtained an accuracy of 100% for discriminating LMC from the patients at high risk for LMC. Considering the difference in magnitude of the mass intensity, the magnitude threshold of 0.01 was empirically determined for search algorithm I.…”